AI Is Not the First Tech Boom in Geoscience

Sure, the robots are coming, but 40 years ago, when seismic and computers came, we adapted. And we will adapt to AI and ML, too.

The current boom of technological advancements in the oil and gas industry is not the first of its kind. We can look back at the dot-com era, advancements in digitization and more to see that the tradeoff for improved operations is usually lost jobs. Increased efficiency means less work, which means downsizing and shifts in the roles remaining. After all, how many people are still skilled with dowsing rods?

It’s tough not to lament the “good ole’ days” when we could get away with doing “just geoscience,” but those good old days were on their way out 60 years ago and truly died about 40 years ago. Let’s look back on some key historic events to see if we can better prepare ourselves to navigate the waters (often rapids!) of change that might lie ahead and are endemic to our industry.

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The current boom of technological advancements in the oil and gas industry is not the first of its kind. We can look back at the dot-com era, advancements in digitization and more to see that the tradeoff for improved operations is usually lost jobs. Increased efficiency means less work, which means downsizing and shifts in the roles remaining. After all, how many people are still skilled with dowsing rods?

It’s tough not to lament the “good ole’ days” when we could get away with doing “just geoscience,” but those good old days were on their way out 60 years ago and truly died about 40 years ago. Let’s look back on some key historic events to see if we can better prepare ourselves to navigate the waters (often rapids!) of change that might lie ahead and are endemic to our industry.

Early Disruptors

Drilling was among the first of the advancements that have disrupted, but bettered, the industry. Today, when an oil seep is reported, the EPA might immediately begin prosecuting the CEO of the oil company with the nearest well, but once upon a time, natural oil seeps were the only source of hydrocarbons. Drake’s Well can be thought of as the parent of the modern oil and gas industry. A rig punched a hole in the Earth to intentionally and forcefully extract hydrocarbons where none might have released on their own, and similar efforts began to follow in rapid succession. While this breakthrough probably eliminated jobs for those who dug ditches and wells by hand at the time, it added others. It spawned an entire industry that required new skills and technology related to drilling rigs, oil transport and managing increased production.

The whaling and coal industries also downsized as a result of drilling, as petroleum products became easier to get and burned more cleanly. The role of exploration geoscientists as historians began: knowing where there were salt brines with oil or where oil seeps had previously been found was a very useful knowledge base. Knowing the “why” wasn’t as necessary, nor even possible yet. These wells produced the first cuttings that could be studied, and seismic wasn’t a thing, but it didn’t take too long before geoscientists came up with some not-entirely-wrong hypotheses about the generation of oil and where to find more.

A seismic shift (pun intended) hit the industry when sound waves were harnessed to illuminate the subsurface (see sidebar). And with that came the computers needed to work with seismic data. By the 1980s, workstations had really made it inescapable: you had to be computer-literate to be a geoscientist. But you also still had to be proficient in geoscience. Clicking around in a program to build a digital map means nothing if you don’t understand the data that went into it, the algorithm behind it and what the map means.

The same is true with artificial intelligence and machine learning. They are simply new tools in the toolbelt, and while learning them won’t guarantee you a job, refusing to learn them could eventually guarantee you a pink slip. The song we’re hearing with AI and ML isn’t new; it’s just a new chorus in the same song. Petroleum geoscience has always required a high degree of adaptability and willingness to learn new skills so we can continue to rigorously test the theories we use to drive this multibillion-dollar industry within which we operate.

AAPG Academy’s recent webinar showcased insights from experts from Nvidia and Rogii, who highlighted ways you can prepare. Nefeli Mordis, head of the subsurface and global energy team at Nvidia, emphasized that you don’t need to start at the beginning with AI: things are moving so fast that learning what’s happening today is more important. Just jump in and try to understand the problem you’re wanting to solve and why. Use search engines to learn which algorithms could be applicable. Learn the advantages and disadvantages of each and pick one or two to work with.

And know that Big Tech is there to help. Microsoft has a ton of free resources, as does Nvidia. You can also hop on almost any supermajor’s website and find their “technology and partnerships” page to find out what they’re investing in. I interpret this as what they view as future needs, so it can help guide your upskilling if something sparks your interest.

Ideally, if you have to pay for anything, your company will support you, but if they don’t, find a way to make it happen anyway. Ultimately, it falls on you to get the skills you need. So, don’t be trepidatious about AI! It’s a new tool, just like the many others before it, and we geoscientists know how to adapt to new tools. We can do it!

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